Remove openai-whisper dependency for log_mel_spectrogram#1846
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musselmanjoey wants to merge 1 commit intoFunAudioLLM:mainfrom
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Remove openai-whisper dependency for log_mel_spectrogram#1846musselmanjoey wants to merge 1 commit intoFunAudioLLM:mainfrom
musselmanjoey wants to merge 1 commit intoFunAudioLLM:mainfrom
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openai-whisper is a heavy (~1.5GB) speech recognition package but CosyVoice only uses whisper.log_mel_spectrogram() — a standard audio preprocessing utility. This causes widespread installation failures (see FunAudioLLM#1844, FunAudioLLM#1266, FunAudioLLM#249, FunAudioLLM#316) due to dependency conflicts, especially on platforms with pre-installed PyTorch (Kaggle, Colab). Replace all whisper.log_mel_spectrogram() calls with a lightweight implementation in cosyvoice/utils/audio_utils.py that uses only torch and torchaudio (already required dependencies). The output is numerically equivalent. The legacy get_tokenizer() function (CosyVoice v1) still needs whisper.tokenizer.Tokenizer, so that import is moved to a lazy import inside the function body — it only triggers if you actually use the v1 tokenizer path. CosyVoice2/3 tokenizers are unaffected. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Summary
whisper.log_mel_spectrogram()calls with a lightweight implementation usingtorch+torchaudio(already required deps)cosyvoice/utils/audio_utils.pywith a drop-inlog_mel_spectrogram()functionopenai-whisper==20231117fromrequirements.txtwhisper.tokenizer.Tokenizerimport (used only by CosyVoice v1'sget_tokenizer()) to a lazy import so it doesn't break module loadingMotivation
openai-whisperis a ~1.5GB speech recognition package, but CosyVoice only uses one utility function from it:whisper.log_mel_spectrogram(). This causes widespread installation failures due to dependency conflicts, especially on platforms with pre-installed PyTorch (Kaggle, Colab, etc).Related issues: #1844, #1266, #249, #316
Details
log_mel_spectrogramis a standard audio preprocessing operation (STFT → mel filterbank → log scaling). The replacement inaudio_utils.pyusestorch.stftandtorchaudio.functional.melscale_fbankswith the same parameters as Whisper (n_fft=400, hop_length=160, 16kHz sample rate), producing numerically equivalent output.Files changed:
cosyvoice/utils/audio_utils.py(new) — sharedlog_mel_spectrogramimplementationcosyvoice/cli/frontend.py— useaudio_utils.log_mel_spectrograminstead ofwhispercosyvoice/dataset/processor.py— same replacementtools/extract_speech_token.py— same replacementcosyvoice/tokenizer/tokenizer.py— lazy import ofwhisper.tokenizer.Tokenizer(only needed for v1 tokenizer path)requirements.txt— removeopenai-whisper🤖 Generated with Claude Code